• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1200-1207
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• 2017

Sensors in a smartphone can be used to measure various physical quantities. In this paper, we propose an object localization scheme in a three dimenstional using a smart phone. The proposed scheme estimates the location of an object by observing it from several different points. The direction to the target object and the locations of the observation points are collected at each observation point using the location sensor and the orientation sensor in the smartphone. Based on these observations, the proposed scheme derives three dimensional line of sight vectors and estimates the location of the target object that minimizes the estimation error. We implemented the proposed scheme on an Android smartphone and tested its performance by estimating the height of a building and characteristics of the proposed approach.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.317-320
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• 2005

The LBS (Location-Based Services) are valuable information services combined the location of moving object with various contents such as map, POI (point of Interest), route and so on. The must general service of LBS is route determination service and its applicable parts are FMS (Fleet Management System), travel advisory system and mobile navigation system. The core function of route determination service is determination of optimal route from source to destination in various environments. The MODB (Moving Object Database) system, core part of LBS composition systems, is able to manage current or past location information of moving object and massive trajectory information stored in MODB is value-added data in CRM, ERP and data mining part. Also this past trajectory information can be helpful to determine optimal route. In this paper, we suggest methods to determine optimal route by querying past trajectory information in MODB system and verify the effectiveness of suggested method.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.996-1002
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• 2015

In this paper, we present an effective system for the 3D scene labeling of objects from RGB-D videos. Our system uses a Markov Random Field (MRF) over a voxel representation of the 3D scene. In order to estimate the correct label of each voxel, the probabilistic graphical model integrates both scores from sliding window-based object detectors and also from object location prior maps. Both the object detectors and the location prior maps are pre-trained from manually labeled RGB-D images. Additionally, the model integrates the scores from considering the geometric constraints between adjacent voxels in the label estimation. We show excellent experimental results for the RGB-D Scenes Dataset built by the University of Washington, in which each indoor scene contains tabletop objects.

• International Journal of Contents
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• v.10 no.4
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• pp.69-74
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• 2014

General location aware systems are only applied to indoor and outdoor environments using more than three transmitters to estimate a fixed object location. Those kinds of systems have environmental restrictions that require an already established infrastructure. To solve this problem, an Object Location Estimation (OLE) algorithm based on PTP (Point To Point) communication has been proposed. However, the problem with this method is that deduction of performance parameters is not enough and location estimation is very difficult because of unknown restriction conditions. From experimental tests in this research, we determined that the performance parameters for restriction conditions are a maximum transmission distance of CSS communication and an optimum moving distance interval between personal locations. In this paper, a system applied OLE algorithm based on PTP communication is implemented using a CSS (Chirp Spread Spectrum) communication module. A maximum transmission distance for CSS communication and an optimum moving distance interval between personal locations are then deducted and studied to estimate a fixed object location for generalization.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.13-18
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• 2015

This paper proposes an optimum vision system analysis and a reliable high-precision positioning system that converges a GNSS and a vision system in order to resolve position error and outdoor shaded areas two disadvantages of GNSS. For location determination of the object, it should receive signal from at least four GNSS. However, in urban areas, exact location determination is difficult due to factors like high buildings, obstacles, and reflected waves. In order to deal with the above problem, a vision system was employed. First, determine an exact position value of a target object in urban areas whose environment is poor for a GNSS. Then, identify such target object by a vision system and its position error is corrected using such target object. A vehicle can identify such target object using a vision system while moving, make location data values, and revise location calculations, thereby resulting in reliable high precision location determination.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.163-167
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• 2002

Recently, owing to performance elevation of telecommunication technology, increase of wireless internet's subscriber and diffusion of wireless device, Interest about LBS (Location Based Service) which take advantage of user's location information and can receive information in concerning with user's location is increasing rapidly. So, MOMS (Moving Object Management System) that manage user's location information is required compulsorily to provide location base service. LBS of childhood such as service to find a friend need only current location, but to provide high-quality service in connection with Data Mining, CRM, We must be able to manage location information of past. In this paper, we design distributed manage system to insert and search Moving Object in a large amount. It has been consisted of CLIM (Current Location Information Manager), PLIM (Past-Location Information Manager) and BLIM (Distributed Location Information Manager). CLIM and PLIM prove performance of searching data by using spatiotemporal-index. DLIM distribute an enormous amount of location data to various database. Thus it keeps load-balance, regulates overload and manage a huge number of location information efficiently.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.63-69
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• 2016

In this paper, we proposed the location tracking system based on MS-Based/Assisted(Mobile Station-Based and Assisted) location trigger service model with context-awareness for the intelligent location tracking of moving objects. It provides the proper resulting value that matches the context of users through the analysis about the situation of the user, physical environment, computing resource and the existing information on user input. In order to provide real-time data, we proposed the location tracking system which realizes the intelligent information such as the expecting arrival time and passing the specific area of the moving object by adopting the location trigger. So, it derives to minimize the costs of communication for the mobile object tracking applications. The proposed location tracking system based on context-awareness can be used for realtime monitoring, intelligent alarm/action, setting up of the optimized moving path, dynamic adjustment of strategies and policies. So it has the advantage to develop the application system which is aimed at optimization of the object tracking and movement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.769-786
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• 2016

Object recognition and object location have always drawn much interest. Also, recently various computational models have been designed. One of the big issues in this domain is the lack of an appropriate model for extracting important part of the picture and estimating the object place in the same environments that caused low accuracy. To solve this problem, a new Salient Based Bag of Visual Word (SBBoVW) model for object recognition and object location estimation is presented. Contributions lied in the present study are two-fold. One is to introduce a new approach, which is a Salient Based Bag of Visual Word model (SBBoVW) to recognize difficult objects that have had low accuracy in previous methods. This method integrates SIFT features of the original and salient parts of pictures and fuses them together to generate better codebooks using bag of visual word method. The second contribution is to introduce a new algorithm for finding object place based on the salient map automatically. The performance evaluation on several data sets proves that the new approach outperforms other state-of-the-arts.

• Journal of Korea Multimedia Society
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• v.24 no.6
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• pp.796-804
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• 2021

In computer vision, visual tracking method addresses the problem of localizing an specific object in video sequence according to the bounding box. In this paper, we propose a tracking method by introducing the feature correlation comparison into the siamese network to increase its matching identification. We propose a way to compute location of object to improve matching performance by a correlation operation, which locates parts for solving the searching problem. The higher layer in the network can extract a lot of object information. The lower layer has many location information. To reduce error rate of the object center point, we built a siamese network that extracts the distribution and location information of target objects. As a result of the experiment, the average center error rate was less than 25%.

• Journal of information and communication convergence engineering
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• v.5 no.4
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• pp.382-388
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• 2007

Indoor location system using wireless sensor network technology was applied for the status evaluation and activity monitoring of elderly person or chronic invalid at home. Location awareness application is transparent to the daily activities, while providing the embedded computing infrastructure with an awareness of what is happening in this space. To locate an object, the active ceiling-mounted reference beacons were placed throughout the building. Reference beacons periodically publish location information on RF and ultrasonic signals to allow application running on mobile or static nodes to study and determine their physical location. Once object-carried passive listener receives the information, it subsequently determines it's location from reference beacons. By using only the sensor nodes without any external network infrastructure the cost of the system was reduced while the accuracy in our experiments. was fairly good and fine grained between 7 and 15 cm for location awareness in indoor environments. Passive architecture used here provides the security of the user privacy while at the server the privacy was secured by providing the authentication using Geopriv approach. This information from sensor nodes is further forwarded to base station where further computation is performed to determine the current position of object and several applications are enabled for context awareness.